TAO Digital Solutions
Website:
taodigitalsolutions.com
Job details:
Dear Folks,
Greetings !!!
We have an exciting openings for BI Developer position @ TAO Digital Solutions (www.taodigitalsolutions.com)
Mode of Work : Hybrid
Location: Chennai / Remote
Skills Required:
- 5+ years in a data analytics, BI, or applied data science role. At least 2 of those years must include hands-on ML model development — segmentation, LTV, churn, or predictive scoring.
- Must provide a GitHub repository or equivalent with at least one end-to-end analytical model — documented, version-controlled, and reproducible without running the code.
- Must provide at least one example of a data narrative or dashboard built for an executive or external client audience — with explanation of the story structure chosen.
- Must have applied an LLM to a real analytics or data science workflow — not a side project or tutorial. Must be able to describe quality evaluation and business impact.
Roles & Responsibilities:
- ▸ Design and build executive-ready dashboards and data stories in Looker (LookML), Tableau, or Cortex Analyst that communicate complex customer behaviour patterns to non-technical audiences — not just displaying numbers, but structuring the narrative around what the data means and what should happen next.
- ▸ Develop a consistent visual language for customer analytics — including standardised KPI definitions, chart typologies, colour systems, and annotation conventions that make insights instantly legible across teams and clients.
- ▸ Create customer-facing analytics deliverables for Account Management team uses in QBRs, executive briefings, and restaurant client strategy sessions. Your work will be seen by the decision-makers of enterprise restaurant brands.
- ▸ Translate model outputs — segmentation clusters, churn probabilities, LTV scores, RFM tiers — into narratives that business stakeholders can act on without needing to understand the underlying methodology.
- ▸ Champion data storytelling best practices across the analytics team: visual hierarchy, progressive disclosure, annotation-first design, and the discipline of leading with the insight rather than the chart.
- ▸ Build and maintain the Looker/LookML semantic layer for customer analytics domains — ensuring metric definitions are canonical, well-documented, and consistent with the organisation-wide definitions owned by the Analytics Engineering team.
- ▸ Maintain and improve self-service analytics capabilities so that account teams can answer their own questions without raising tickets.
- ▸ Build and maintain customer segmentation models using clustering techniques (K-Means, DBSCAN, hierarchical clustering) on multi-tenant restaurant ordering data — producing actionable customer segments that Marketing and Product can activate.
- ▸ Apply LLM and AI tools (Gemini, GPT-4, or equivalent) to accelerate and enhance analytics workflows — including automated insight generation, natural language querying of dashboards, and AI-assisted anomaly explanation. Bring genuine hands-on LLM experience, not theoretical familiarity.
- ▸ Use Python for the full applied ML workflow: data wrangling (pandas, NumPy), visualization (matplotlib, seaborn, plotly), model development (scikit-learn, XGBoost, statsmodels), and result communication. Write clean, documented, reproducible code that Analytics Engineers and Data Scientists can build on.
- ▸ Own the customer analytics intelligence function for proactively identifying patterns in ordering behaviour, engagement trends, campaign response, and churn risk before stakeholders ask. Surface findings with a point of view, not just a chart.
- ▸ Support ad-hoc analysis for customers, executives, and internal stakeholders — going beyond data retrieval to provide interpretive framing and actionable recommendations.
- ▸ Build and maintain KPI frameworks for customer health, engagement, and retention — defining the metrics that matter and ensuring they are measured consistently across all restaurant clients and platforms.
- ▸ Write high-quality SQL to extract, transform, and validate data from Redshift, BigQuery, and Snowflake — including complex window functions, CTEs, and query optimisation for analytical workloads.
- ▸ Collaborate with Analytics Engineers on LookML architecture for customer analytics domains — providing the analytical requirements that inform model design, validating that semantic layer definitions match business intent, and flagging discrepancies between warehouse data and business expectations.
- ▸ Collaborate with the Analytics Engineers (Marketing & Activation) on the customer journey data model — ensuring that Segment, Braze, Acoustic, and GA4 data flowing through the warehouse is correctly modelled for segmentation and LTV use cases.
- ▸ Contribute to coding standards and peer review processes — your Python and SQL work should meet the same quality bar as engineering code: version-controlled, tested, and documented.
Interested candidates please forward your updated resume to the following email ID (mohan.kaliappan@taodigitalsolutions.com) ASAP
Click on Apply to know more.